
doi: 10.1108/eb026768
A probabilistic model previously used in relevance feedback is adapted for use in automatic indexing of documents (in the sense of imitating human indexers). The model fits with previous work in this area (the ‘adhesion coefficient’ method), in effect merely suggesting a different way of arriving at the adhesion coefficients. Methods for the application of the model are proposed. The independence assumptions used in the model are interpreted, and the possibility of a dependence model is discussed.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
